Exome sequencing identifies rare variants in multiple genes in atrioventricular septal defect
Bibliographic record
Abstract
PURPOSE: The genetic etiology of atrioventricular septal defect (AVSD) is unknown in 40% cases. Conventional sequencing and arrays have identified the etiology in only a minority of nonsyndromic individuals with AVSD. METHODS: Whole-exome sequencing was performed in 81 unrelated probands with AVSD to identify potentially causal variants in a comprehensive set of 112 genes with strong biological relevance to AVSD. RESULTS: A significant enrichment of rare and rare damaging variants was identified in the gene set, compared with controls (odds ratio (OR): 1.52; 95% confidence interval (CI): 1.35-1.71; P = 4.8 × 10(-11)). The enrichment was specific to AVSD probands, compared with a cohort without AVSD with tetralogy of Fallot (OR: 2.25; 95% CI: 1.84-2.76; P = 2.2 × 10(-16)). Six genes (NIPBL, CHD7, CEP152, BMPR1a, ZFPM2, and MDM4) were enriched for rare variants in AVSD compared with controls, including three syndrome-associated genes (NIPBL, CHD7, and CEP152). The findings were confirmed in a replication cohort of 81 AVSD probands. CONCLUSION: Mutations in genes with strong biological relevance to AVSD, including syndrome-associated genes, can contribute to AVSD, even in those with isolated heart disease. The identification of a gene set associated with AVSD will facilitate targeted genetic screening in this cohort.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".